This disclosure relates generally to estimating a lift in foot traffic at a store, and more particularly to estimating foot traffic lift at the store in response to an advertisement campaign at an online system.
Businesses often use behaviors of their customers to influence services provided to the customers. Businesses may provide advertisements to users at an online system to increase traffic to their stores. Any business that provides such advertisements may be interested in estimating a lift in foot traffic at a physical location of its stores in response to the advertisement campaign to measure the effectiveness of its advertisement campaign.
Conventional techniques for estimating foot traffic lift use direct measures of foot traffic such as tracking a number of visits to a store's physical location by estimating a number of users within a predefined region around the store's physical location. In such a technique, a user is counted as a visitor to a store if the user's device is detected to be within a predefined region around the physical location of the store. The accuracy of such a conventional technique depends on a frequency with which the user's device reports its location. For example, the accuracy of the foot traffic lift estimate increases as the reporting frequency increases. It is important for businesses with brick-and-mortar stores engaging in advertisement campaigns at online systems to be able to estimate foot traffic lift in response to such campaigns accurately irrespective of a frequency with which the user's device reports its location.